I didn't mean acoustic data, but I was thinking of long term global datasets like this: http://www.isc.ac.uk/iscgem/overview.php http://www.isc.ac.uk/iscgem/ov

I didn't mean acoustic data, but I was thinking of long term global datasets like this: http://www.isc.ac.uk/iscgem/overview.php http://www.isc.ac.uk/iscgem/overview.php It covers over 26,000 earthquakes going back roughly a century, but I admit I'm somewhat disappointed that it only seems to cover Magnitude Mw ≥ 5.5 quakes. A machine learning algorithm may need even more data points than that to spot reasonable patterns, even if it was given the location of landmasses and fault lines to help it, but I wouldn't be surprised if someone could generate a model which can predict future quakes at least somewhat better than random chance (factoring in averages for a given location).